Databases are used for writing, storing, maintaining, and analyzing data related to business processes. Usually, a row-based or an object-oriented database is used for writing and storing data. In the row-based or the object-oriented database each record or entity may be recorded as a row or an object at a time. However, reading or retrieving data from the row or object-oriented database may be inefficient and time consuming. In the row-based or the object-oriented database, various unwanted data (e.g., some undesired data from a row or an object) may be required to be read before retrieving the required data from that row or object. Also, it may be required to read a preceding row or object to get to the required or desired row or object. Therefore, the row or object-oriented database may be inefficient and time consuming for reading data, retrieving data, and performing data analytics.
Usually, column database is used in data analytics to retrieve required data efficiently. In column database, the desired data can be retrieved directly from the column containing that data without reading the preceding column. Therefore, usually, it is desired to write or maintain data in the object-oriented database in real time and replicate the data in the column database so that efficient data analysis can be performed using the column database. The object-oriented database and the column database are required to be synchronized so that correct data analysis can be performed using the column database. Usually, a machine or a server is required or configured to connect and synchronize the object-oriented database and the column database. However, installing and configuring the machine or the server is an expensive and an arduous task. Further, if any data is updated in the object-oriented database, the entire row or object related to the updated data is read to update the corresponding data in the column database which again is a time consuming task.